AIMC Topic: Adult

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Interpretable machine learning insights into the association between PFAS exposure and diabetes mellitus.

Ecotoxicology and environmental safety
BACKGROUND: Diabetes Mellitus (DM) is a global health concern with rising prevalence, and its link to PFAS exposure remains unclear. No machine learning (ML) models have yet been developed to predict DM based on PFAS exposure.

International Consensus Histopathological Criteria for Subtyping Idiopathic Multicentric Castleman Disease Based on Machine Learning Analysis.

American journal of hematology
Idiopathic multicentric Castleman disease (iMCD) is a rare lymphoproliferative disorder classified into three recognized clinical subtypes-idiopathic plasmacytic lymphadenopathy (IPL), TAFRO, and NOS. Although clinical criteria are available for subt...

Artificial Intelligence Language Models to Translate Professional Radiology Mammography Reports Into Plain Language - Impact on Interpretability and Perception by Patients.

Academic radiology
RATIONALE AND OBJECTIVES: This study aimed to evaluate the interpretability and patient perception of AI-translated mammography and sonography reports, focusing on comprehensibility, follow-up recommendations, and conveyed empathy using a survey.

Automated quantitative analysis of peri-articular bone microarchitecture in HR-pQCT knee images.

Computer methods and programs in biomedicine
UNLABELLED: Applying HR-pQCT to image the knee necessitates the development and validation of novel image analysis workflows. Here, we present and validate the first automated workflow for in vivo quantitative assessment of peri-articular bone densit...

Mindset matters: exploring the link between mindsets, learning intentions, and performance in biomedical science students.

Advances in physiology education
Students' "mindset" (self-beliefs and attitudes toward their abilities) can impact academic achievement, with those possessing a growth mindset more likely to succeed. It has been postulated that students with a growth mindset, who believe they can i...

Efficacy of rTMS on SCZ symptoms: Insights from connectome mapping.

Psychiatry research
Repetitive transcranial magnetic stimulation (rTMS) is a potential treatment for schizophrenia (SCZ), yet its efficacy and underlying mechanisms remain uncertain. This study evaluates the impact of rTMS targeting the right orbitofrontal cortex (OFC) ...

Searching for peripheral proteomic markers of primary aldosteronism.

Endocrine
PURPOSE: Primary aldosteronism (PA) is prevalent among hypertensive patients, and associated with worsened cardiovascular outcomes compared to essential hypertension (HT). Screening and diagnostics for PA are currently complicated and invasive, why n...

Modeling decision-making during unprotected left turns using interpretable deep learning and uncertainty quantification.

Accident; analysis and prevention
Unprotected left turns present challenges to drivers, as they must manage potential conflicts at intersections, which requires a decision-making process different from that in other driving scenarios. While many studies have modeled human decision-ma...

Assessment of outcomes and machine Learning-based models to predict local failure risk following stereotactic radiosurgery for small brain metastases.

Journal of neuro-oncology
INTRODUCTION: We assessed the outcomes of stereotactic radiosurgery (SRS) for small intact brain metastases (SBM) (≤ 2 cm) and developed machine learning (ML) algorithms to predict the probability of local failure (LF).